# ZOE - what's going on here? something we can delete? The Olney transit corridor runs along Chew Av , and Olney Av between Locust Av and Front St. The corridor serves the routes 18, and 26. There are 21 total bus stops along the corridor, with the average bus trip running past 10 stops spanning 1.08 miles.
# map of routes that exist in this corridor
leaflet() %>%
setView(lng = -75.14511, lat = 40.03905, zoom = 13) %>%
addProviderTiles(providers$Stamen.Toner) %>%
addCircleMarkers(daily_stop_analytics, lat = daily_stop_analytics$stop_lat, lng = daily_stop_analytics$stop_lon, radius = (daily_stop_analytics$total_ons + daily_stop_analytics$total_offs)/100, color = "blue") #addPolylines(data = routes_w_ridership, color = "#4377bc", weight = 4, layerId = link_stop_data$fromto, opacity = 0.5)
# also add chart/table of global averages for context of subcorridorsThese charts illustrate characteristics for the Olney corridor as a whole, such as average speed and ridership. Average speed, as well as ridership., vary both by route and by time of day.
table_1 <- full_corridor_results$route_analytics[[1]] %>% bind_rows(full_corridor_results$analytics[[1]] %>% mutate(route_id = "Total"))
kable(table_1, booktabs = TRUE, align = 'c',format.args = list(big.mark = ","),digits=1) %>%
kable_styling(latex_options = "scale_down") %>%
row_spec(dim(table_1)[1], bold = T) %>% # format last row
column_spec(1, italic = T) %>% # format first column
scroll_box(width = "100%", height = "300px")| route_id | daily_ridership | trips | routes_served | service_hours | riders_per_hour | on_off | dwell_observed_mean | dwell_predicted_mean | dwell_hybrid_mean | dwell_per_onoff | onoff_per_trip | onoff_per_tripstop | avg_segment_speed | avg_speed_10_pct | avg_speed_25_pct | avg_speed_75_pct | avg_speed_90_pct |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | 6,826 | 235 | 18 | 19.8 | 345.1 | 3,896.5 | 0 | 83.7 | 83.7 | 0.2 | 16.6 | 1.5 | 12.0 | 9.6 | 10.3 | 12.6 | 14.5 |
| 26 | 4,966 | 227 | 26 | 20.1 | 247.4 | 2,072.4 | 0 | 71.0 | 71.0 | 0.1 | 9.1 | 0.9 | 11.1 | 9.6 | 10.3 | 11.9 | 13.2 |
| Total | 11,792 | 462 | 18, 26 | 39.9 | 295.9 | 5,968.9 | 0 | 77.5 | 77.5 | 0.2 | 12.9 | 1.2 | 11.6 | 9.6 | 10.3 | 12.1 | 14.0 |
Speed and reliability are two of the most important aspects governing how attractive transit is to the customer.
There is, however, an important distinction between transit speed and transit reliability: - speed is how fast the vehicle is moving through the corridor - reliability is how consistent those speeds are, throughout a day or another period of time.
Oftentimes, qualitative research on transit finds that riders remember their worst trip much more vividly than their average (or even their best) trips. This is where reliability is key - providing customers with a consistent trip time is just as important as a fast trip time, because when they budget time for future trips, they have to be reasonably sure that the time budgeted will represent the majority of potential travel time outcomes.
Corridor-level travel time is simply the amount of time it takes the bus to travel from one end of the corridor to another. In this case, it is show separated by route and by direction and is averaged for each hour.
Service hours are a measure of how much transit is operated on the corridor. It is simply the sum of all of the runtime on the corridor over a period of time. Service hours is a product of how much transit is provide, but it is also a product of the speed of operations on a corridor. Transit productivity is often measured in terms of service hours because it is the most direct input into the cost of running the service.
Interpretation
| route_id | daily_ridership | trips | routes_served | service_hours | riders_per_hour | on_off | dwell_observed_mean | dwell_predicted_mean | dwell_hybrid_mean | dwell_per_onoff | onoff_per_trip | onoff_per_tripstop | avg_segment_speed | avg_speed_10_pct | avg_speed_25_pct | avg_speed_75_pct | avg_speed_90_pct |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | 6,826 | 235 | 18 | 19.8 | 345.1 | 3,896.5 | 0 | 83.7 | 83.7 | 0.2 | 16.6 | 1.5 | 12.0 | 9.6 | 10.3 | 12.6 | 14.5 |
| 26 | 4,966 | 227 | 26 | 20.1 | 247.4 | 2,072.4 | 0 | 71.0 | 71.0 | 0.1 | 9.1 | 0.9 | 11.1 | 9.6 | 10.3 | 11.9 | 13.2 |
| Total | 11,792 | 462 | 18, 26 | 39.9 | 295.9 | 5,968.9 | 0 | 77.5 | 77.5 | 0.2 | 12.9 | 1.2 | 11.6 | 9.6 | 10.3 | 12.1 | 14.0 |
Interpretation
| route_id | daily_ridership | trips | routes_served | service_hours | riders_per_hour | on_off | dwell_observed_mean | dwell_predicted_mean | dwell_hybrid_mean | dwell_per_onoff | onoff_per_trip | onoff_per_tripstop | avg_segment_speed | avg_speed_10_pct | avg_speed_25_pct | avg_speed_75_pct | avg_speed_90_pct |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | 8,505 | 235 | 18 | 11.6 | 731.8 | 5,515.5 | 0 | 82.8 | 82.8 | 0.3 | 23.5 | 3.9 | 10.3 | 8.0 | 8.7 | 11.3 | 12.9 |
| 26 | 6,992 | 229 | 26 | 15.1 | 462.2 | 5,542.4 | 0 | 75.2 | 75.2 | 0.3 | 24.2 | 3.5 | 11.5 | 9.3 | 10.2 | 12.5 | 14.2 |
| Total | 15,497 | 464 | 18, 26 | 26.8 | 579.3 | 11,057.9 | 0 | 79.0 | 79.0 | 0.3 | 23.8 | 3.4 | 10.9 | 8.4 | 9.3 | 12.1 | 13.8 |
Interpretation
| route_id | daily_ridership | trips | routes_served | service_hours | riders_per_hour | on_off | dwell_observed_mean | dwell_predicted_mean | dwell_hybrid_mean | dwell_per_onoff | onoff_per_trip | onoff_per_tripstop | avg_segment_speed | avg_speed_10_pct | avg_speed_25_pct | avg_speed_75_pct | avg_speed_90_pct |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18 | 5,981 | 223 | 18 | -10.5 | -568.3 | 2,036.3 | 0 | 52.2 | 52.2 | 0.2 | 9.1 | 1.5 | 10.5 | 8.2 | 8.9 | 11.4 | 14.1 |
| 26 | 4,896 | 229 | 26 | 14.2 | 345.8 | 2,224.6 | 0 | 53.7 | 53.7 | 0.2 | 9.7 | 1.4 | 10.0 | 8.2 | 8.9 | 10.8 | 12.5 |
| Total | 10,877 | 452 | 18, 26 | 3.6 | 2,994.6 | 4,261.0 | 0 | 53.0 | 53.0 | 0.2 | 9.4 | 1.4 | 10.3 | 8.2 | 8.9 | 11.0 | 13.3 |